Traditional information technology infrastructures for entities usually require several operating environments, vendor resource deployment, authentication repositories and mechanisms, application servers, and databases for storing, indexing, and updating massive amounts of data on a daily bases. All of these systems and processes must work together in order to operate a large entity's information technology and be able to store, index, and manage data received by the entity.
Typically, databases load data received by the entity for indexing continuously in order to keep up with the volume of data an entity receives and/or tracks on a daily bases. Frequently, the data stored by the entity may need to be updated. This may occur for a variety of reason, including mistakes in the loading, changing flags, changes in the information within the rows, or the like.
The process of database loading and updating takes time, central processing units (CPU) away from the infrastructure, logging time, and in some cases has redundancies and locking issues associated with the process.
Therefore, a need exists for an improved database input and database update system that limits the time, memory, and logging required for core input and update functions to be completed and implemented.